Validation of Quantitative Microbial Risk Assessment Using Epidemiological Data from Outbreaks of Waterborne Gastrointestinal Disease

Two risk assessments: Evaluating the use of indicator HF183 Bacteroides versus pathogen measurements for modelling recreational illness risks in an urban watershed

The purpose of this study was to evaluate the performance of HF183 Bacteroides for estimating pathogen exposures during recreational water activities. We compared the use of Bacteroides-based exposure assessment to exposure assessment that relied on pathogen measurements. We considered two types of recreational water sites: those impacted by combined sewer overflows (CSOs) and those not impacted by CSOs. Samples from CSO-impacted and non-CSO-impacted urban creeks were analysed by quantitative polymerase chain reaction (qPCR) for HF183 Bacteroides and eight human gastrointestinal pathogens. Exposure assessment was conducted two ways for each type of site (CSO-impacted vs. non-CSO impacted): 1) by estimating pathogen concentrations from HF183 Bacteroides concentrations using published ratios of HF183 to pathogens in sewage and 2) by estimating pathogen concentrations from qPCR measurements. QMRA (quantitative microbial risk assessment) was then conducted for swimming, wading, and fishing exposures. Overall, mean risk estimates varied from 0.27 to 53 illnesses per 1,000 recreators depending on exposure assessment, site, activity, and norovirus dose-response model. HF183-based exposure assessment identified CSO-impacted sites as higher risk, and the recommended HF183 risk-based threshold of 525 genomic copies per 100 mL was generally protective of public health at the CSO-impacted sites but was not as protective at the non-CSO-impacted sites. In the context of our urban watershed, HF183-based exposure assessment over- and under-estimated risk relative to exposure assessment based on pathogen measurements, and the etiology of predicted pathogen-specific illnesses differed significantly. Across all sites, the HF183 model overestimated risk for norovirus, adenovirus, and Campylobacter jejuni, and it underestimated risk for E. coli and Cryptosporidium. To our knowledge, this study is the first to directly compare health risk estimates using HF183 and empirical pathogen measurements from the same waterways. Our work highlights the importance of site-specific hazard identification and exposure assessment to decide whether HF183 is applicable for monitoring risk.

Vaccine value profile for norovirus

Norovirus is attributed to nearly 1 out of every 5 episodes of diarrheal disease globally and is estimated to cause approximately 200,000 deaths annually worldwide, with 70,000 or more among children in developing countries. Noroviruses remain a leading cause of sporadic disease and outbreaks of acute gastroenteritis even in industrialized settings, highlighting that improved hygiene and sanitation alone may not be fully effective in controlling norovirus. Strengths in global progress towards a Norovirus vaccine include a diverse though not deep pipeline which includes multiple approaches, including some with proven technology platforms (e.g., VLP-based HPV vaccines). However, several gaps in knowledge persist, including a fulsome mechanistic understanding of how the virus attaches to human host cells, internalizes, and induces disease.

Producing ratio measures of effect with quantitative microbial risk assessment

Estimating the risk of infections or other outcomes incident to pathogen exposure is a primary goal of quantitative microbial risk assessment (QMRA). Such estimates are useful to predict population-level risks, to evaluate exposures based on normative or tolerable risk guidelines, and to interpret the likely public health relevance of microbial measurements in environmental media. To evaluate alternative control measures (interventions), ratio estimates of effect (e.g., odds and risk ratios) are needed that are more broadly interpretable in the health sciences and consistent with convention in epidemiology. In this paper, we propose a general method for estimating widely used ratio measures of effect derived from stochastic QMRA approaches, including the generation of appropriate confidence intervals. Such QMRA-derived ratios can be used as a basis for evaluating interventions via hypothesis testing and for inclusion in systematic reviews and meta-analyses in a form consistent with risk estimation approaches commonly used in epidemiology.

Producing ratio measures of effect with quantitative microbial risk assessment

Estimating the risk of infections or other outcomes incident to pathogen exposure is a primary goal of quantitative microbial risk assessment (QMRA). Such estimates are useful to predict population-level risks, to evaluate exposures based on normative or tolerable risk guidelines, and to interpret the likely public health relevance of microbial measurements in environmental media. To evaluate alternative control measures (interventions), ratio estimates of effect (e.g., odds and risk ratios) are needed that are more broadly interpretable in the health sciences and consistent with convention in epidemiology. In this paper, we propose a general method for estimating widely used ratio measures of effect derived from stochastic QMRA approaches, including the generation of appropriate confidence intervals. Such QMRA-derived ratios can be used as a basis for evaluating interventions via hypothesis testing and for inclusion in systematic reviews and meta-analyses in a form consistent with risk estimation approaches commonly used in epidemiology.

Quantitative microbial risk assessment of outdoor aerosolized pathogens in cities with poor sanitation

The aeromicrobiological transmission pathway of enteric pathogens in places with unsafe sanitation services is poorly understood. In an attempt to partly fill this knowledge gap, we assessed the potential public health impact of bioaerosols near open waste canals (OWCs) using Quantitative Microbial Risk Assessment (QMRA). We used data acquired in La Paz, Bolivia to characterize the risk of disease that aerosolized enteric pathogens may pose through food, fomites and inhalation (all followed by ingestion). Three reference pathogens were selected to conduct the assessment: enterotoxigenic Escherichia coli (ETEC), Shigella flexneri, and Campylobacter jejuni. Inhalation followed by ingestion had the highest median infection risk per event i.e. 3 × 10^-5 (3 infections for every 100,000 exposures), compared to contaminated food e.g. 5 × 10^-6 and fomites e.g. 2 × 10^-7, all for C. jejuni infections. Our sensitivity analysis showed that bacterial fluxes from the air were the most influential factor on risk. Our results suggest that fecal bacterial aerosols from OWCs present non-negligible risks of infection in La Paz, with median annual infection risks by C. jejuni being 18 (food), and 100 (inhalation) times greater than the EPA's standard for drinking water (1 × 10^-4). We included two of the QMRA models presented here in a novel web application we developed for user-specified application in different contexts.

Statewide Quantitative Microbial Risk Assessment for Waterborne Viruses, Bacteria, and Protozoa in Public Water Supply Wells in Minnesota

Infection risk from waterborne pathogens can be estimated via quantitative microbial risk assessment (QMRA) and forms an important consideration in the management of public groundwater systems. However, few groundwater QMRAs use site-specific hazard identification and exposure assessment, so prevailing risks in these systems remain poorly defined. We estimated the infection risk for 9 waterborne pathogens based on a 2-year pathogen occurrence study in which 964 water samples were collected from 145 public wells throughout Minnesota, USA. Annual risk across all nine pathogens combined was 3.3 × 10^-1 (95% CI: 2.3 × 10^-1 to 4.2 × 10^-1), 3.9 × 10^-2 (2.3 × 10^-2 to 5.4 × 10^-2), and 1.2 × 10^-1 (2.6 × 10^-2 to 2.7 × 10^-1) infections person^-1 year^-1 for noncommunity, nondisinfecting community, and disinfecting community wells, respectively. Risk estimates exceeded the U.S. benchmark of 10^-4 infections person^-1 year^-1 in 59% of well-years, indicating that the risk was widespread. While the annual risk for all pathogens combined was relatively high, the average daily doses for individual pathogens were low, indicating that significant risk results from sporadic pathogen exposure. Cryptosporidium dominated annual risk, so improved identification of wells susceptible to Cryptosporidium contamination may be important for risk mitigation.

A Bibliometric Analysis of the Literature on Norovirus Disease from 1991-2021

Norovirus (NoV) is one of the oldest recognized diseases and the leading causal pathogen for acute gastroenteritis (AGE) worldwide. Though numerous studies have been reported on NoV disease, limited research has explored the publication trends in this area. As a result, the objective of this work was to fill the void by conducting a bibliometric study in publication trends on NoV studies as well as discovering the hotspots. The Web of Science central assemblage database was hunted for publications from 1991 to 2021 with “norovirus” in the heading. Microsoft Excel 2016, VOSviewer, R Bibliometrix, and Biblioshiny packages were deployed for the statistical analysis of published research articles. A total of 6021 published documents were identified in the Web of Science database for this thirty-year study period (1991–2021). The analyses disclosed that the Journal of Medical Virology was the leading journal in publications on norovirus studies with a total of 215 published articles, the Journal of Virology was the most cited document with 11,185 total citations. The United States of America (USA) has the most significant productivity in norovirus publications and is the leading country with the highest international collaboration. Analysis of top germane authors discovered that X. Jiang (135) and J. Vinje (119) were the two top relevant authors of norovirus publications. The commonly recognized funders were US and EU-based, with the US emerging as a top funder. This study reveals trends in scientific findings and academic collaborations and serves as a leading-edge model to reveal trends in global research in the field of norovirus research. This study points out the progress status and trends on NoV research. It can help researchers in the medical profession obtain a comprehensive understanding of the state of the art of NoV. It also has reference values for the research and application of the NoV visualization methods. Further, the research map on AGE obtained by our analysis is expected to help researchers efficiently and effectively explore the NoV field.

Quantitative Microbial Risk Assessment for Contaminated Private Wells in the Fractured Dolomite Aquifer of Kewaunee County, Wisconsin

BACKGROUND

Private wells are an important source of drinking water in Kewaunee County, Wisconsin. Due to the region's fractured dolomite aquifer, these wells are vulnerable to contamination by human and zoonotic gastrointestinal pathogens originating from land-applied cattle manure and private septic systems.

OBJECTIVE

We determined the magnitude of the health burden associated with contamination of private wells in Kewaunee County by feces-borne gastrointestinal pathogens.

METHODS

This study used data from a year-long countywide pathogen occurrence study as inputs into a quantitative microbial risk assessment (QMRA) to predict the total cases of acute gastrointestinal illness (AGI) caused by private well contamination in the county. Microbial source tracking was used to associate predicted cases of illness with bovine, human, or unknown fecal sources.

RESULTS

Results suggest that private well contamination could be responsible for as many as 301 AGI cases per year in Kewaunee County, and that 230 and 12 cases per year were associated with a bovine and human fecal source, respectively. Furthermore, Cryptosporidium parvum was predicted to cause 190 cases per year, the most out of all 8 pathogens included in the QMRA.

DISCUSSION

This study has important implications for land use and water resource management in Kewaunee County and informs the public health impacts of consuming drinking water produced in other similarly vulnerable hydrogeological settings. https://doi.org/10.1289/EHP7815.

Implementation of quantitative microbial risk assessment (QMRA) for public drinking water supplies: Systematic review

In the more than 15 years since its introduction, quantitative microbial risk assessment (QMRA) has become a widely used technique for assessing population health risk posed by waterborne pathogens. However, the variation in approaches taken for QMRA in relation to drinking water supply is not well understood. This systematic review identifies, categorises, and critically synthesises peer-reviewed and academic case studies of QMRA implementation for existing distributed public drinking water supplies. Thirty-nine English-language, peer-reviewed and academic studies published from 2003 to 2019 were identified. Key findings were synthesised in narrative form. The overall designs of the included studies varied widely, as did the assumptions used in risk calculation, especially in relation to pathogen dose. There was also substantial variation in the degree to which the use of location-specific data weighed with the use of assumptions when performing risk calculation. In general, the included studies' complexity did not appear to be associated with greater result certainty. Factors relating to pathogen dose were commonly influential on risk estimates whereas dose-response parameters tended to be of low relative influence. In two of the included studies, use of the 'susceptible fraction' factor was inconsistent with recognised guidance and potentially led to the underestimation of risk. While approaches and assumptions used in QMRA need not be standardised, improvement in the reporting of QMRA results and uncertainties would be beneficial. It is recommended that future authors consider the water supply QMRA reporting checklist developed for the current review. Consideration of the broad types of uncertainty relevant to QMRA is also recommended. Policy-makers should consider emergent discussion on acute microbial health-based targets when setting normative guidelines. The continued representation of QMRA case studies within peer-reviewed and academic literature would also enhance future implementation. Further research is needed on the optimisation of QMRA resourcing given the application context.

Outbreak-Based Giardia Dose-Response Model Using Bayesian Hierarchical Markov Chain Monte Carlo Analysis

Giardia is a zoonotic gastrointestinal parasite responsible for a substantial global public health burden, and quantitative microbial risk assessment (QMRA) is often used to forecast and manage this burden. QMRA requires dose-response models to extrapolate available dose-response data, but the existing model for Giardia ignores valuable dose-response information, particularly data from several well-documented waterborne outbreaks of giardiasis. The current study updates Giardia dose-response modeling by synthesizing all available data from outbreaks and experimental studies using a Bayesian random effects dose-response model. For outbreaks, mean doses (D) and the degree of spatial and temporal aggregation among cysts were estimated using exposure assessment implemented via two-dimensional Monte Carlo simulation, while potential overreporting of outbreak cases was handled using published overreporting factors and censored binomial regression. Parameter estimation was by Markov chain Monte Carlo simulation and indicated that a typical exponential dose-response parameter for Giardia is r = 1.6 × 10^-2 [3.7 × 10^-3 , 6.2 × 10^-2 ] (posterior median [95% credible interval]), while a typical morbidity ratio is m = 3.8 × 10^-1 [2.3 × 10^-1 , 5.5 × 10^-1 ]. Corresponding (logistic-scale) variance components were σ_r = 5.2 × 10^-1 [1.1 × 10^-1 , 9.6 × 10^-1 ] and σ_m = 9.3 × 10^-1 [7.0 × 10^-2 , 2.8 × 10⁰ ], indicating substantial variation in the Giardia dose-response relationship. Compared to the existing Giardia dose-response model, the current study provides more representative estimation of uncertainty in r and novel quantification of its natural variability. Several options for incorporating variability in r (and m) into QMRA predictions are discussed, including incorporation via Monte Carlo simulation as well as evaluation of the current study's model using the approximate beta-Poisson.